IBM C1000-144 : IBM Machine Learning Data Scientist v1

  • Exam Code: C1000-144
  • Exam Name: IBM Machine Learning Data Scientist v1
  • Updated: Jul 23, 2026   Q&As: 0 Questions and Answers

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IBM C1000-144 Exam Syllabus Topics:
SectionWeightObjectives
Evaluate business problem including ethical implications21%- Business requirements understanding
  • 1. AI design thinking process
    • 2. Understand business requirements
      • 3. AI Ladder assessment
        • 4. Understand available data
          • 5. Ethical challenges in AI/ML problem framing
            Model Implementation26%- Machine learning methods
            • 1. Supervised learning: regression
              • 2. Dimensionality reduction techniques
                • 3. Supervised learning: classification
                  • 4. Unsupervised learning: clustering
                    Model Refinement and Deployment18%- Model lifecycle operations
                    • 1. Feature engineering and selection
                      • 2. Model explainability
                        • 3. Tool selection
                          • 4. Hyperparameter tuning
                            • 5. Training environment configuration
                              Model Monitoring in Production17%- Operational monitoring
                              • 1. Production monitoring
                                • 2. Bias detection and fairness assessment
                                  • 3. Model performance evaluation
                                    Exploratory Data Analysis and Data Preparation18%- Data preparation techniques
                                    • 1. Data cleaning, labeling, anonymization
                                      • 2. Data balancing and partitioning
                                        • 3. Data visualization

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